Remote mapping and analysis from the surface of the earth of hydrocarbons reservoired at depth remains a difficult technical task. This is so despite recent advances in 3D seismic imaging, seismic direct hydrocarbon indicator (DHI) and amplitude variation with offset (AVO) analyses, and seismic attribute mapping and interpretation. Seismic detection difficulties arise in part from the fact that the mechanical properties of reservoirs, to which the seismic probe responds, are often only slightly modified when hydrocarbons replace formation waters, especially in the case of oil. The modification may be of the order of only 10's of percent. Subtle mechanical effects related to seismic wave propagation and reflection can mask DHI and AVO signatures or even produce misleading signatures. For example, low gas saturation in water sands can produce false seismic DHIs. Because of such effects, drill-well success rates are too low and exploration costs are too high in many basins. In addition, rapid and low-cost assessment of discovered undeveloped hydrocarbon reserves requires good knowledge of reservoir properties at large distances from the discovery well. Acquiring this knowledge is problematic using only seismic data. There is an urgent need to remotely measure and map other reservoir formation properties that are sensitive to hydrocarbons, and to combine interpretation of these other properties with interpretations of seismic data and their mapped attributes. One particularly important formation property is electrical resistivity, which is strongly related to the pore fluid type and saturation.
The bulk electrical resistivity of reservoirs is often increased substantially when hydrocarbons are present. The increase can be of the order of 100's to 1000's of percent. However, increased formation resistivity alone may not uniquely indicate hydrocarbons. For instance, carbonates, volcanics, and coals can also be highly resistive. Nevertheless, spatial correlation of high formation resistivity with potential traps imaged by seismic data, or with seismic DHI or AVO effects at reservoir depth, provides strong evidence of the presence of oil or gas and valuable information on their concentrations. For example, a low gas saturation high-porosity sandstone reservoir encased in shale can produce a strong seismic DHI and an AVO curve indicative of gas. However, it would also have low electrical resistivity and hence would be a high-risk drill-well prospect.
Most hydrocarbon reservoirs are inter-bedded with shale stringers or other non-permeable intervals and hence are electrically anisotropic at the macroscopic scale. Thus, it is important to measure both the vertical (transverse) and horizontal (longitudinal) electrical resistivities of the reservoir interval. Remote measurement of the vertical and horizontal resistivities of the reservoir interval, combined with estimation of the resistivity of the non-permeable bedding, would provide quantitative bounds on the reservoir's fluid content, such as the hydrocarbon pore volume. However, there is no existing technology for remotely measuring reservoir formation resistivity from the land surface of the seafloor at the vertical resolution required in hydrocarbon exploration and production. Based on the thicknesses of known reservoirs and predicted future needs, this required resolution would be equal to or less than two percent of depth from the earth's surface or seafloor. For example, this would resolve a 200-ft net reservoir thickness (vertical sum of hydrocarbon bearing rock thicknesses within the reservoir interval) or less at a typical 10,000-ft reservoir depth.
Overviews of electromagnetic imaging technology are given by M. N. Nabighian (ed.), Electromagnetic Methods in Applied Geophysics, Vols. 1 & 2, SEG Investigations in Geophysics No. 3, 1988; A. G. Nekut and B. R. Spies, Proceedings IEEE, v. 77, 338-362, 1989; and by M. S. Zhdanov and G. V. Keller, The Geoelectrical Methods in Geophysical Exploration, Elsevier, 1994. Imaging of electrically conductive objects such as ore bodies has been the dominant application for electromagnetic methods. In applications for hydrocarbon exploration, most of the technology was developed to image large geological structures in regions where seismic data are low in quality or are absent, and little other geological or geophysical information is available.
Direct exploration for hydrocarbons using surface-based electromagnetic imaging has been attempted since the 1930s, but with little commercial success. This lack of success is due to the low spatial resolution and the ambiguous interpretation results of current electromagnetic methods, when applied in stand-alone and spatially undersampled ways to the geological imaging problem. Low subsurface resolution is one consequence of the diffusive nature of the low frequency electromagnetic waves, that is, below 1 kHz, required to penetrate the earth to reservoir depths. The vertical resolution of such electromagnetic waves is relatively insensitive to bandwidth, unlike the seismic case, but is very sensitive to the accuracy and precision of phase and amplitude measurements and to the inclusion of constraints from other data. That is, the unconstrained geophysical electromagnetic data inverse problem is mathematically ill posed, with many possible geologic structures fitting electromagnetic data equally well. Consequently, the vertical resolution of unconstrained electromagnetic imaging is typically no better than 10 percent of depth. This gives a resolution of only a 1000-ft net reservoir thickness at a typical 10,000-ft reservoir depth. However, within a given resolved layer, conventional resistivity measurement accuracy can be within a factor of two, which is adequate for oil and gas exploration.
Electromagnetic technology that is applicable to direct reservoir imaging uses electrically grounded controlled sources to produce vertical and horizontal current flow in the subsurface at the reservoir depth. The five embodiments of this technology, well known within the electromagnetic imaging community, are: (1) the LOTEM method described by K. M. Strack, Exploration with Deep Transient Electromagnetics, Elsevier, 1992; (2) the SIROTEM method, described by Buselli in U.S. Pat. No. 4,247,821; (3) CGG's TRANSIEL® system, described in U.S. Pat. No. 4,535,5293; (4) the EMI method, described by Tasci et al. in U.S. Pat. No. 5,563,513; and (5) the WEGA-D method described by B. W. Smith and J. Dzwinel in WEGA-D SYSTEM®, WEGA-D Geophysical Research Ltd., 1984. A newer version of WEGA-D named PowerProbe® has been developed by the Canadian company Enertec, a successor to WEGA-D Geophysical Research. All five methods suffer from the vertical resolution limitation of approximately 10% of depth cited above, which makes them unsuitable for direct reservoir imaging except for unusually thick reservoirs. This resolution limitation results from one or more of the following deficiencies in each method: (1) lack of means to focus the electromagnetic input energy at the target reservoir; (2) spatial undersampling of the surface electromagnetic response fields; (3) measurement of only a few components (usually one) of the multi-component electromagnetic surface fields that comprise full tensor electromagnetic responses at each reservoir (except for WEGA-D/PowerProbe); (4) data processing using 1-D, 2-D, or pattern recognition algorithms rather than full 3-D imaging methods; and (5) lack or paucity of explicit depth information and resistivity parameter values incorporated into the data processing to constrain the inversion results.
Another serious limitation in these five methods is their use of high-impedance contact electrodes and connecting wires, with greater than 1 Ohm total series resistance, to transmit the source current into the subsurface. This output impedance is primarily a result of the small surface area of the electrodes that contact (i.e. ground to) the earth. High output impedance severely limits the electrical current at the reservoir depth, which in turn reduces the strengths of the surface electromagnetic responses to the subsurface reservoir for a given source power. Current limitation due to high-impedance sources also results in reduced depths of exploration, especially in electrically conductive sedimentary basins. The effective depth of electromagnetic exploration increases as a fractional power of source strength, between M1/5 and M1/3 for grounded electric dipole sources where M is the dipole moment, that is, current multiplied by dipole length. The exponent depends upon which surface field component is measured, but in general short-offset (or “near-field”) electromagnetic receiver responses have the best sensitivity to deep targets, as shown in B. R. Spies, Geophysics v. 54, 872-888, 1989.
V. S. Mogilatov and B. Balashov, J. Appl. Geophys., v. 36, 31-41, 1996; and Mogilatov's Russian patent 2,084,929-C1 describe the use of surface electric concentric ring dipoles and radial electric bipoles. A. G. Tarkov, Bull. Acad. Sci. U.S.S.R., Geophys. Ser., no. 8, 11, 1957, R. N. Gupta and P. K. Bhattacharya, Geophysics, v. 28, 608-616, 1963, and by A. Dey et al., Geophysics, v. 40, 630-640, 1975 describe the use of opposite-polarity collinear surface electric bipoles (“unipoles”). However, ring electrodes described by Mogilatov and Balashov do not contain discussions of, much less calculations for, the optimum electrode dimensions needed to maximize the vertical electric field or current density at the target (reservoir) depth. The unipole methods described by Tarkov, Gupta, Bhattacharya, and Dey et al. do not include discussions of or calculations for the effects of changing the source frequency, or the effects of using finite-length unipoles (second electrodes not at infinite distance), on the optimum configuration needed to maximize the vertical electric field or current density at the target depth.
S. K. Verma and S. P. Sharma, Geophysics, v. 60, 381-389, 1995 and H. Maurer and D. E. Boerner, Geophys. J. Int., v. 132, 458-468, 1998 discuss optimization of surface electromagnetic source array configurations in order to best focus energy onto subsurface targets. However, Verma and Sharma restrict their discussion to subsurface conducting layers, and do not include unipole or concentric ring dipole arrays in their calculations. Maurer and Boerner discuss the more general problem of optimization of surface electromagnetic surveys for imaging subsurface targets, but do not discuss unipole, multiple radial bipole, or concentric ring dipole sources.
Conventional geophysical electromagnetic data processing finds the minimum earth structure, that is, the simplest resistivity model, which is consistent with the measured data within the experimental error bounds, but without explicit incorporation of a priori information. Incorporation of hard constraints into the data processing significantly improves spatial resolution and resistivity accuracy, which are not simply related to signal wavelength or bandwidth as in the seismic case. Examination of well log and other data shows that, in most cases, major seismic boundaries are also major resistivity boundaries. In addition, interpretation of seismic, gravity, and magnetic data would provide good knowledge of the major lithologies present in a perspective area before drilling. Applying constraints for a large number, (10's to 100's) of layers and other major geologic boundaries (for instance, faults) would be novel for electromagnetic imaging of hydrocarbon reservoirs.
Two previous methods have described the incorporation of seismic constraints to improve spatial resolution in low-frequency electromagnetic geophysical inversion. Although not applied to hydrocarbon reservoir imaging, a method was developed by G. M. Hoversten et. al., Geophysics, v. 63, 826-840, 1998a; and SEG Annual Meeting Expanded Abstracts, v. 1, 425-428, 1998b to improve 2-D natural-source electromagnetic (magnetotelluric) imaging of the base of salt structures in the offshore Gulf of Mexico. Vertical resolution of the salt base improves by a factor of 2 to 3 when the depth to the top of salt is constrained by 3-D seismic data and when the salt resistivity is fixed. Natural-source methods such as that of Hoversten et al. lack the vertical resolution required for direct imaging of resistive hydrocarbon reservoirs, because they measure the earth's response to the flow of horizontal subsurface electrical currents that are insensitive to regions of increased resistivity. D. L. Alumbaugh and G. A. Newman, Geophys. J. Int., v. 128, 355-363, 1997; and SEG Annual Meeting Expanded Abstracts, v. 1, 448-451, 1998 have described the use of seismic constraints to improve resolution in cross-well electromagnetic imaging within hydrocarbon reservoirs, in a manner similar to that of Hoversten et al. for surface magnetotelluric data. However, the cross-well method requires the existence of at least two wells that penetrate the reservoir.
Estimation of the reservoir's fluid type, saturation, and shaliness factor from surface geophysical measurements has been previously conducted using only seismic reflection data, in particular various seismic interval attributes (amplitude widths, ratios, phases, etc.). Here, the shaliness factor is the ratio of net hydrocarbon bearing zone thickness (pay) to gross reservoir thickness. It is well known in the industry that the electromagnetic response of a vertically layered earth depends on the direction of the resistivity measurement. See, for instance, M. S. Zhdanov and G. V. Keller (1994, op. cit.). However, there is no existing remote (surface-based) electromagnetic method for measuring both the separate vertical and horizontal resistivities of a reservoir interval at depth. Directional resistivity measurements for reservoirs have been restricted to in-situ methods, such as well logging.
Specific technologies for indirect electromagnetic detection of reservoired hydrocarbons at depth have also been developed, but these rely on the detection of electrically altered zones (“chimneys”) above reservoirs caused by the purported slow leakage of hydrocarbons upward from the reservoir. The existence and relationships of alteration chimneys to reservoired hydrocarbons have not been unequivocally demonstrated. Changes in resistivity (increases and decreases) and polarizability (or induced polarization) are claimed by the practitioners of chimney detection to occur at various locations within such chimneys. Electromagnetic methods to locate chimneys were developed by Sternberg et al., as described in their U.S. Pat. No. 4,446,434, and Tasci et al., as described in their U.S. Pat. No. 5,563,513. The TRANSIEL® and WEGA-D/PowerProbe systems can also be used to detect hydrocarbon chimneys. These methods suffer the same depth resolution limitations as listed above, for the reasons cited in the preceding paragraph.